Job Title- Senior AI Engineer/ ML Engineer

5+years
Remote

EST Job Timing - 7:30pm to 4:30am IST

Position Overview

The AI Engineer is responsible for designing, developing, deploying, and optimizing artificial intelligence and machine learning solutions that deliver measurable business value. This role combines software engineering expertise, machine learning knowledge, and generative AI capabilities to build scalable AI applications, automation solutions, and intelligent systems.
The AI Engineer will collaborate with data scientists, AI architects, product teams, business stakeholders, and engineering teams to translate business requirements into production-ready AI solutions.

Key Responsibilities

AI Solution Development

• Design, develop, and deploy AI/ML models and generative AI applications.
• Build AI-powered solutions using large language models (LLMs), machine learning frameworks, and cloud AI platforms.
• Develop AI agents, intelligent workflows, retrieval-augmented generation (RAG) systems, and automation solutions.
• Integrate AI capabilities into enterprise applications and business processes.
• Evaluate, fine-tune, and optimize AI models for performance, accuracy, scalability, and cost efficiency.

Machine Learning Engineering

• Develop and maintain machine learning pipelines from data preparation through model deployment.
• Implement model training, testing, validation, monitoring, and continuous improvement processes.
• Apply machine learning techniques including natural language processing (NLP), classification, prediction, recommendation, and anomaly detection.
• Conduct model evaluation using appropriate metrics and business outcomes.

Generative AI Engineering

• Develop applications leveraging foundation models and LLM technologies.
• Design effective prompt engineering strategies and reusable prompt frameworks.
• Build RAG architectures using enterprise data sources, vector databases, and knowledge repositories.
• Implement AI guardrails, security controls, responsible AI practices, and governance requirements.
• Optimize AI applications for reliability, explainability, and user experience.

Software Engineering & Integration

• Write clean, maintainable, and production-quality code.
• Develop APIs, microservices, and AI-enabled applications.
• Integrate AI solutions with enterprise platforms, databases, and cloud environments.
• Support DevOps, MLOps, CI/CD, and automated deployment processes.
• Troubleshoot performance, reliability, and scalability issues.

Collaboration & Delivery

• Partner with AI Architects to implement enterprise AI strategies and technical designs.
• Work with business analysts and stakeholders to translate business needs into AI solutions.
• Participate in Agile development processes including planning, development, testing, and demonstrations.
• Document AI solutions, technical designs, models, and operational procedures.
• Stay current with emerging AI technologies, frameworks, and industry best practices.

Required Qualifications

Technical Skills

• Bachelor's degree in computer science, Artificial Intelligence, Data Science, Engineering, or related field.
• 5+ years of experience developing software, machine learning models, or AI applications.
• Strong programming skills in Python and experience with AI/ML libraries.
• Experience with machine learning frameworks such as:
  • PyTorch
  • TensorFlow
  • Scikit-learn
  • Hugging Face Transformers
• Experience developing applications using large language models and generative AI technologies.
• Experience with APIs, cloud platforms, databases, and software development practices.
• Understanding of data structures, algorithms, and software engineering principles.

Generative AI Skills

• Experience with LLM application development.
• Knowledge of prompt engineering techniques.
• Experience building RAG solutions.
• Familiarity with vector databases and embedding technologies.
• Understanding of AI evaluation, model limitations, hallucination mitigation, and responsible AI practices.

Cloud & DevOps Skills

• Experience with one or more cloud platforms:
  • Microsoft Azure AI Services
  • Amazon Web Services (AWS AI/ML Services)
  • Google Cloud AI Platform
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Understanding of MLOps concepts including model deployment, monitoring, and lifecycle management.

Preferred Qualifications

• Master's degree in AI, Computer Science, Data Science, or related field.
• Experience implementing enterprise-scale AI solutions.
• Experience with AI agents and autonomous workflow automation.
• Experience with enterprise data platforms and knowledge management systems.
• Experience with security, privacy, and compliance requirements for AI systems.
• Familiarity with AI governance frameworks and regulatory considerations.

Core Competencies

• Strong problem-solving and analytical skills.
• Ability to translate complex technical concepts into business value.
• Strong software engineering discipline.
• Curiosity and passion for emerging AI technologies.
• Ability to work collaboratively across technical and business teams.
• Strong communication and documentation skills.

Success Metrics

Success in this role will be measured by:

• Delivery of reliable, scalable AI solutions.
• Improved business process efficiency through AI automation.
• AI model accuracy, performance, and user adoption.
• Reduction in operational costs through intelligent automation.
• Compliance with AI security, governance, and responsible AI standards.

Experience Level

Mid-Level AI Engineer: 3–5 years' experience

Senior AI Engineer: 5–8+ years' experience with enterprise AI architecture, LLM applications, and production AI deployments.